Trend analysis of seasonal rainfall and temperature pattern in Damota Gale districts of Wolaita Zone, Ethiopia

Kendall Test ◽

Maximum Temperature ◽

Temperature Pattern ◽

Positive Trend ◽

Increasing Trend ◽

Abstract Background: This paper investigated the recent trends of precipitation and temperature on Damota Gale districts of Wolaita Zone. This study used the observed historical meteorological data from 1987 to 2019 to analyze the trends. The magnitude of the variability or fluctuations of the factors varies according to locations. Hence, examining the spatiotemporal dynamics of meteorological variables in the context of changing climate, particularly in countries where rain fed agriculture is predominant, is vital to assess climate-induced changes and suggest feasible adaptation strategies. Results: Both rainfall and temperature data for period of 1987 to 2019 were analyzed in this study. Statistical trend analysis techniques namely Mann–Kendall test and Sen's slope estimator were used to examine and analyze the problems. The long-term trend of rainfall and temperature was evaluated by linear regression and Mann–Kendall test. The temperature was shown a positive trend for the both annual and seasonal periods and had a statistical significance at 95%.Conclusion: This study concluded that there were a declining rainfall in the three seasons; spring, summer and winter but in autumn it shows increasing trends and rapid warming, especially in the last 32 years. The detailed analysis of the data for 32 years indicate that the annual maximum temperature and annual minimum temperature have shown an increasing trend, whereas the Damota Gale seasonal maximum and minimum temperatures have shown an increasing trend. The findings of this study will serve as a reference for climate researchers, policy and decision makers.

Trend analysis of seasonal rainfall and temperature pattern in Damota Gale districts of Wolaita Zone, Ethiopia

10.21203/rs.3.rs-454366/v1 ◽

2021 ◽

Author(s):

Elias Bojago ◽

Dalga YaYa

Keyword(s):

Trend Analysis ◽

Meteorological Data ◽

Kendall Test ◽

Maximum Temperature ◽

Temperature Pattern ◽

Positive Trend ◽

Increasing Trend ◽

Abstract This paper investigated the recent trends of precipitation and temperature on Damota Gale districts of Wolaita Zone. This study used the observed historical meteorological data from 1987 to 2019 to analyze the trends. The magnitude of the variability or fluctuations of the factors varies according to locations. Hence, examining the spatiotemporal dynamics of meteorological variables in the context of changing climate, particularly in countries where rain-fed agriculture is predominant, is vital to assess climate-induced changes and suggest feasible adaptation strategies. Both rainfall and temperature data for a period of 1987 to 2019 were analyzed in this study. Statistical trend analysis techniques namely Mann–Kendall test and Sen's slope estimator were used to examine and analyze the problems. The long-term trend of rainfall and temperature was evaluated by linear regression and Mann–Kendall test. The temperature was shown a positive trend for both annual and seasonal periods and had a statistical significance of 95%. This study concluded that there was a declining rainfall in the three seasons; spring, summer and winter but in autumn it shows increasing trends and rapid warming, especially in the last 32 years. The detailed analysis of the data for 32 years indicate that the annual maximum temperature and annual minimum temperature have shown an increasing trend, whereas the Damota Gale seasonal maximum and minimum temperatures have shown an increasing trend. The findings of this study will serve as a reference for climate researchers, policy and decision-makers.

Assessment of Trends and Variability of Rainfall and Temperature for the District of Mandi in Himachal Pradesh, India

Slovak Journal of Civil Engineering ◽

10.1515/sjce-2017-0014 ◽

2017 ◽

Vol 25 (3) ◽

pp. 15-22 ◽

Cited By ~ 4

Author(s):

John Mohd Wani ◽

V. K. Sarda ◽

Sanjay. K. Jain

Keyword(s):

Time Series Data ◽

Kendall Test ◽

Himachal Pradesh ◽

Annual Rainfall ◽

Series Data ◽

Maximum Temperature ◽

Sen’S Slope ◽

Increasing Trend ◽

Abstract Climate variability, particularly, that of the annual air temperature and precipitation, has received a great deal of attention worldwide. The magnitude of the variability of the factors changes according to the locations. The present study focuses on detecting the trends and variability in the annual temperature and rainfall for the district of Mandi in Himachal Pradesh, India. This study used annual and monsoon time series data for the time period 1981-2010 and modified the Mann-Kendall test and Sen's slope estimator in analyzing the problem. The results of the analysis indicate that the annual maximum temperature (TMX) and annual minimum temperature (TMN) for the period of 30 years have shown an increasing trend, whereas the monsoon’s maximum and minimum temperatures have shown a decreasing trend, although it is statistically not significant. The amount of annual rainfall does not show any significant trend, but the monsoonal rainfall has shown an increasing trend that is also statistically not significant. The resulting Mann-Kendall test statistic (Z) and Sen’s slope estimate (Q) of all the parameters studied indicate that changes are occurring in the magnitude and timing of the precipitation and temperature events at the Mandi station.

Innovative Trend Analysis of Precipitation in the Lake Issyk-Kul Basin, Kyrgyzstan

Atmosphere ◽

10.3390/atmos11040332 ◽

2020 ◽

Vol 11 (4) ◽

pp. 332 ◽

Cited By ~ 10

Author(s):

Yilinuer Alifujiang ◽

Jilili Abuduwaili ◽

Balati Maihemuti ◽

Bilal Emin ◽

Michael Groll

Keyword(s):

Trend Analysis ◽

Resource Planning ◽

Kendall Test ◽

Trend Test ◽

Lake Basin ◽

Positive Trend ◽

Monthly Precipitation ◽

Innovative Trend Analysis ◽

Mann Kendall Test ◽

Increasing Trends

The analysis of various characteristics and trends of precipitation is an essential task to improve the utilization of water resources. Lake Issyk-Kul basin is an upper alpine catchment, which is more susceptible to the effects of climate variability, and identifying rainfall variations has vital importance for water resource planning and management in the lake basin. The well-known approaches linear regression, Şen’s slope, Spearman’s rho, and Mann-Kendall trend tests are applied frequently to try to identify trend variations, especially in rainfall, in most literature around the world. Recently, a newly developed method of Şen-innovative trend analysis (ITA) provides some advantages of visual-graphical illustrations and the identification of trends, which is one of the main focuses in this article. This study obtained the monthly precipitation data (between 1951 and 2012) from three meteorological stations (Balykchy, Cholpon-Ata, and Kyzyl-Suu) surrounding the Lake Issyk-Kul, and investigated the trends of precipitation variability by applying the ITA method. For comparison purposes, the traditional Mann–Kendall trend test also used the same time series. The main results of this study include the following. (1) According to the Mann-Kendall trend test, the precipitation of all months at the Balykchy station showed a positive trend (except in January (Zc = −0.784) and July (Zc = 0.079)). At the Cholpon-Ata and Kyzyl-Suu stations, monthly precipitation (with the same month of multiple years averaged) indicated a decreasing trend in January, June, August, and November. At the monthly scale, significant increasing trends (Zc > Z0.10 = 1.645) were detected in February and October for three stations. (2) The ITA method indicated that the rising trends were seen in 16 out of 36 months at the three stations, while six months showed decreasing patterns for “high” monthly precipitation. According to the “low” monthly precipitations, 14 months had an increasing trend, and four months showed a decreasing trend. Through the application of the ITA method (January, March, and August at Balykchy; December at Cholpon-Ata; and July and December at Kyzyl-Suu), there were some significant increasing trends, but the Mann-Kendall test found no significant trends. The significant trend occupies 19.4% in the Mann-Kendall test and 36.1% in the ITA method, which indicates that the ITA method displays more positive significant trends than Mann–Kendall Zc. (3) Compared with the classical Mann-Kendall trend results, the ITA method has some advantages. This approach allows more detailed interpretations about trend detection, which has benefits for identifying hidden variation trends of precipitation and the graphical illustration of the trend variability of extreme events, such as “high” and “low” values of monthly precipitation. In contrast, these cannot be discovered by applying traditional methods.

Homogeneity Evaluation of Historical Rainfall and Temperature Series in Mato Grosso

Journal of Experimental Agriculture International ◽

10.9734/jeai/2019/v35i330205 ◽

2019 ◽

pp. 1-7

Author(s):

Elizangela Selma da Silva ◽

José Holanda Campelo Júnior ◽

Francisco De Almeida Lobo ◽

Ricardo Santos Silva Amorim

Keyword(s):

Trend Analysis ◽

Minimum Temperature ◽

Statistical Tests ◽

Kendall Test ◽

Maximum Temperature ◽

Data Series ◽

Positive Trend ◽

Mato Grosso ◽

Temperature Climate ◽

Precipitation And Temperature

The homogeneity investigation of a series can be performed through several nonparametric statistical tests, which serve to detect artificial changes or non-homogeneities in climatic variables. The objective of this work was to evaluate two methodologies to verify the homogeneity of the historical climatological series of precipitation and temperature in Mato Grosso state. The series homogeneity evaluation was performed using the following non-parametric tests: Wald-Wolfowitz (for series with one or no interruption), Kruskal-Wallis (for series with two or more interruptions), and Mann-Kendall (for time series trend analysis). The results of the precipitation series homogeneity analysis from the National Waters Agency stations, analyzed by the Kruskal-Wallis and Wald-Wolfowitz tests, presented 61.54% of homogeneous stations, being well distributed throughout Mato Grosso state, whereas those of the trend analysis allowed to identify that 87.57% of the rainfall-gauging stations showed a concentrated positive trend, mainly in the rainy season. Out of the conventional stations of the National Institute of Meteorology of Mato Grosso, seven were homogeneous for the precipitation variable, five for maximum temperature and four stations were homogeneous for minimum temperature. For the trend analysis in the 11 stations, positive trends of random nature were observed, suggesting increasing alterations in the analyzed variables. Therefore, the trend analysis performed by the Mann-Kendall test in the precipitation, and maximum and minimum temperature climate series, indicated that several data series showed increasing trends, suggesting a possible increase in precipitation and temperature values over the years. The results of the Kruskal-Wallis and Wald-Wolfowitz tests for homogeneity presented more than 87% of homogeneous stations.

Monotonic Trend Analysis of Temperature Series over Mandya City, Karnataka

International Journal for Research in Applied Science and Engineering Technology ◽

10.22214/ijraset.2021.36633 ◽

2021 ◽

Vol 9 (VII) ◽

pp. 1530-1535

Author(s):

Madhusudhan M S

Keyword(s):

Climate Change ◽

Trend Analysis ◽

Agricultural Sector ◽

Kendall Test ◽

Temperature Series ◽

Maximum Temperature ◽

Positive Trend ◽

Significance Level ◽

Monotonic Trend ◽

Indirect Impacts

Climate change is mostly driven by global warming. Climate change is one of the most critical long-term development issues, particularly for developing countries like India. India is one of the world's most climatically diverse countries, making it sensitive to climatic change and impacting the livelihoods of millions of people who rely on agriculture. Temperature and its fluctuation have direct and indirect impacts on crop development in the agricultural sector. Understanding the temperature and its variability in a changing environment would aid in improved decision-making and suggest feasible adaption strategies. The present study focuses on temperature trend analysis in Mandya city, Karnataka, India. The analysis was carried out through the non-parametric Mann-Kendall test and Sen's slope estimator. The findings demonstrate that, there has been a rising trend in temperature in the study area over the last 30 years as a result of climate change. From the analysis, there is a significant positive trend for all the seasons considered for the significance level of 90%, 95% and 99%. The magnitude of the increasing trend will be in the range of 0.46 °C/year for the average time series. Also, there will be an average increase of 0.07 °C/year for the various scenarios considered in Mandya city for the Maximum temperature series.

Long-Term Trend Analysis in Annual and Seasonal Precipitation, Maximum and Minimum Temperatures in the Southwest United States

Climate ◽

10.3390/cli8120142 ◽

2020 ◽

Vol 8 (12) ◽

pp. 142

Author(s):

Koffi Djaman ◽

Komlan Koudahe ◽

Ansoumana Bodian ◽

Lamine Diop ◽

Papa Malick Ndiaye

Keyword(s):

United States ◽

Trend Analysis ◽

Minimum Temperature ◽

Test Method ◽

Maximum Temperature ◽

Crop Season ◽

Southwest United States ◽

Increasing Trend

The objective of this study is to perform trend analysis in the historic data sets of annual and crop season [May–September] precipitation and daily maximum and minimum temperatures across the southwest United States. Eighteen ground-based weather stations were considered across the southwest United States for a total period from 1902 to 2017. The non-parametric Mann–Kendall test method was used for the significance of the trend analysis and the Sen’s slope estimator was used to derive the long-term average rates of change in the parameters. The results showed a decreasing trend in annual precipitation at 44.4% of the stations with the Sen’s slopes varying from −1.35 to −0.02 mm/year while the other stations showed an increasing trend. Crop season total precipitation showed non-significant variation at most of the stations except two stations in Arizona. Seventy-five percent of the stations showed increasing trend in annual maximum temperature at the rates that varied from 0.6 to 3.1 °C per century. Air cooling varied from 0.2 to 1.0 °C per century with dominant warming phenomenon at the regional scale of the southwest United States. Average annual minimum temperature had increased at 69% of the stations at the rates that varied from 0.1 to 8 °C over the last century, while the annual temperature amplitude showed a decreasing trend at 63% of stations. Crop season maximum temperature had significant increasing trend at 68.8% of the stations at the rates varying from 0.7 to 3.5 °C per century, while the season minimum temperature had increased at 75% of the stations.

Climate Variability and Farmers’ Perception in Southern Ethiopia

Advances in Meteorology ◽

10.1155/2019/7341465 ◽

2019 ◽

Vol 2019 ◽

pp. 1-19 ◽

Cited By ~ 1

Author(s):

Befikadu Esayas ◽

Belay Simane ◽

Ermias Teferi ◽

Victor Ongoma ◽

Nigussie Tefera

Keyword(s):

Climate Variability ◽

Sampling Technique ◽

Farm Households ◽

Maximum Temperature ◽

Southern Ethiopia ◽

Positive Trend ◽

Temperature And Precipitation ◽

Binary Logit

The study aims to analyze climate variability and farmers’ perception in Southern Ethiopia. Gridded annual temperature and precipitation data were obtained from the National Meteorological Agency (NMA) of Ethiopia for the period between 1983 and 2014. Using a multistage sampling technique, 403 farm households were surveyed to substantiate farmers’ perceptions about climate variability and change. The study applied a nonparametric Sen’s slope estimator and Mann–Kendall’s trend tests to detect the magnitude and statistical significance of climate variability and binary logit regression model to find factors influencing farm households’ perceptions about climate variability over three agroecological zones (AEZs). The trend analysis reveals that positive trends were observed in the annual maximum temperature, 0.02°C/year (p<0.01) in the lowland and 0.04°C/year (p<0.01) in the highland AEZs. The positive trend in annual minimum temperature was consistent in all AEZs and significant (p<0.01). An upward trend in the annual total rainfall (10 mm/year) (p<0.05) was recorded in the midland AEZ. Over 60% of farmers have perceived increasing temperature and decreasing rainfall in all AEZs. However, farmers’ perception about rainfall in the midland AEZ contradicts with meteorological analysis. Results from the binary logit model inform that farmers’ climate change perceptions are significantly influenced by their access to climate and market information, agroecology, education, agricultural input, and village market distance. Based on these results, it is recommended to enhance farm households’ capacity by providing timely weather and climate information along with institutional actions such as agricultural extension services.

Temporal Analysis of Temperature and Precipitation Trends in Shaheed Benazir Abad Sindh, Pakistan

Engineering, Technology & Applied Science Research ◽

10.48084/etasr.1388 ◽

2017 ◽

Vol 7 (6) ◽

pp. 2171-2176 ◽

Cited By ~ 2

Author(s):

S. R. Samo ◽

N. Bhatti ◽

A. Saand ◽

M. A. Keerio ◽

D. K. Bangwar

Keyword(s):

Diurnal Temperature Range ◽

Kendall Test ◽

Maximum Temperature ◽

Linear Regression Method ◽

Positive Trend ◽

Diurnal Temperature ◽

Temperature Range ◽

Temperature And Precipitation ◽

Mann Kendall Test ◽

Rainy Days

Temperature and precipitation variations have a huge environmental, social and economic impact. This study aims to analyze the temporal variation of temperature and precipitation in Shaheed Benazir Abad district by using the linear regression method, the trend magnitude, the Mann-Kendall test and the Sen’s estimator of slope. The annual precipitation and monthly temperature data of Shaheed Benazir Abad for the period of 1996-2014 are considered. The result shows that the Diurnal temperature range of all months is decreasing due to the increasing of monthly minimum temperature at a faster rate than the monthly maximum temperature. However, the Diurnal temperature range of extreme events is increasing. The results obtained by using Mann-Kendall test revealed that rainfall exhibits significant positive trend. The trends of rainfall and rainy days show that the amount of rainfall is increasing much more rapidly than that of rainy days which indicates the occurrence of heavy events.

Trends in rainfall amount and number of rainy days in river basins of India (1951–2004)

Hydrology Research ◽

10.2166/nh.2011.067 ◽

2011 ◽

Vol 42 (4) ◽

pp. 290-306 ◽

Cited By ~ 54

Author(s):

Vijay Kumar ◽

Sharad K. Jain

Keyword(s):

Monsoon Rainfall ◽

Kendall Test ◽

River Basins ◽

Rainfall Amount ◽

Annual Rainfall ◽

Positive Trend ◽

Significant Positive Trend ◽

Increasing Trend ◽

Rainy Days

This study aims to determine trends in annual and seasonal rainfall and rainy days over different river basins across India. The data used consists of daily gridded rainfall at 1° × 1° resolution for the period 1951–2004. Sen's non-parametric estimator of slope was used to estimate the magnitude of trend whose statistical significance was assessed by the Mann–Kendall test. Among 22 basins studied, 15 showed a decreasing trend in annual rainfall; only one basin showed a significant decreasing trend at 95% confidence level. Of the 6 basins showing an increasing trend, 1 basin showed a significant positive trend. The monsoon rainfall increased over 6 basins, decreased over 16 basins and a decreasing trend for 2 basins was found statistical significant. With the exception of Ganga, Brahmaputra and EFR4, all river basins experienced the same direction of trend in monsoon and annual rainfall. Four river basins experienced increasing (non-significant) trend in annual rainy days; three basins did not show any change in annual rainy days whereas 15 basins have shown a decreasing trend in annual rainy days. The decreasing trend in three basins was statistically significant. Most of the basins have shown the same direction of trend in rainfall and rainy days at the annual and seasonal scale.

Effects of the prewhitening method, the time granularity and the time segmentation on the Mann-Kendall trend detection and the associated Sen's slope

10.5194/amt-2020-178 ◽

2020 ◽

Cited By ~ 2

Author(s):

Martine Collaud Coen ◽

Elisabeth Andrews ◽

Alesssandro Bigi ◽

Gonzague Romanens ◽

Giovanni Martucci ◽

...

Keyword(s):

Time Series ◽

Trend Analysis ◽

Parametric Method ◽

Kendall Test ◽

Trend Detection ◽

Temporal Segmentation ◽

Sen’S Slope ◽

Power Of The Test ◽

Abstract. The most widely used non-parametric method for trend analysis is the Mann-Kendall test associated with the Sen's slope. The Mann-Kendall test requires serially uncorrelated time series, whereas most of the atmospheric processes exhibit positive autocorrelation. Several prewhitening methods have been designed to overcome the presence of lag-1 autocorrelation. These include a prewhitening, a detrending and/or a correction for the detrended slope and the original variance of the time series. The choice of which prewhitening method and temporal segmentation to apply has consequences for the statistical significance, the value of the slope and of the confidence limits. Here, the effects of various prewhitening methods are analyzed for seven time series comprising in-situ aerosol measurements (scattering coefficient, absorption coefficient, number concentration and aerosol optical depth), Raman Lidar water vapor mixing ratio and the tropopause and zero degree levels measured by radio-sounding. These time series are characterized by a broad variety of distributions, ranges and lag-1 autocorrelation values and vary in length between 10 and 60 years. A common way to work around the autocorrelation problem is to decrease it by averaging the data over longer time intervals than in the original time series. Thus, the second focus of this study is evaluation of the effect of time granularity on long-term trend analysis. Finally, a new algorithm involving three prewhitening methods is proposed in order to maximize the power of the test, to minimize the amount of erroneous detected trends in the absence of a real trend and to ensure the best slope estimate for the considered length of the time series.